CN110675043B - Method and system for determining power grid power failure key line based on cascading failure model - Google Patents

Method and system for determining power grid power failure key line based on cascading failure model Download PDF

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CN110675043B
CN110675043B CN201910874650.1A CN201910874650A CN110675043B CN 110675043 B CN110675043 B CN 110675043B CN 201910874650 A CN201910874650 A CN 201910874650A CN 110675043 B CN110675043 B CN 110675043B
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line
simulation
power grid
failure
power
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CN110675043A (en
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何晓峰
程韧俐
夏成军
黎寿涛
马伟哲
史军
吴新
郑晓辉
程维杰
黄双
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Shenzhen Power Supply Bureau Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0635—Risk analysis of enterprise or organisation activities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/067—Enterprise or organisation modelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02H—EMERGENCY PROTECTIVE CIRCUIT ARRANGEMENTS
    • H02H7/00—Emergency protective circuit arrangements specially adapted for specific types of electric machines or apparatus or for sectionalised protection of cable or line systems, and effecting automatic switching in the event of an undesired change from normal working conditions
    • H02H7/26—Sectionalised protection of cable or line systems, e.g. for disconnecting a section on which a short-circuit, earth fault, or arc discharge has occured
    • H02H7/28—Sectionalised protection of cable or line systems, e.g. for disconnecting a section on which a short-circuit, earth fault, or arc discharge has occured for meshed systems

Abstract

The invention provides a method for determining a power failure key line of a power grid based on a cascading failure model, which comprises the steps of obtaining a power grid model to be calculated and corresponding relevant model information thereof, and obtaining a topological structure of the power grid according to the power grid model and the corresponding relevant model information thereof; and determining the total number of days of cascading failure simulation mode simulation formed by the topological structure of the power grid, simulating by taking each day as a unit, obtaining the line number of the disconnected line output by each day of simulation after the total number of days of simulation is finished, further counting the number of the line numbers of the disconnected line output by each day of simulation, and outputting the disconnected line with the maximum number of the line numbers as the power grid power failure key line. By implementing the method and the device, the key line which has important influence on the cascading failure of the power system can be identified, and data support is provided for line capacity expansion.

Description

Method and system for determining power grid power failure key line based on cascading failure model
Technical Field
The invention relates to the technical field of power risk control, in particular to a method and a system for determining a power grid power failure key line based on a cascading failure model.
Background
At present, a power grid enters a rapid development period of cross-large-area interconnection and ultra-high and extra-high voltage alternating current and direct current hybrid power transmission, and the complexity of the power grid is increased rapidly, so that the risk of large-area power failure accidents caused by cascading failures is increased gradually.
In order to facilitate the study of the cascading failures of the power grid, different cascading failure theoretical models and power failure risk indexes of the power system are provided. The model and the method are started from elements, the overall reliability of the system is measured through a certain computing technology, and the physical significance of the model and the method is clear.
However, for a large power grid system, on one hand, the severity of a blackout accident can be covered to a certain extent by a traditional probabilistic index, and on the other hand, the exponential increase of the calculation complexity is caused by the increase of the dimension, so that the online application is difficult. Therefore, the key lines which have important influence on the cascading failure of the power system cannot be identified, and the weak links of the power system cannot be reconstructed.
Disclosure of Invention
The technical problem to be solved by the embodiments of the present invention is to provide a method and a system for determining a power failure key line of a power grid based on a cascading failure model, which can identify a key line that has an important influence on cascading failures of a power system, provide data support for line capacity expansion, and implement transformation of weak links of the power system.
In order to solve the technical problem, an embodiment of the present invention provides a method for determining a power failure key line of a power grid based on a cascading failure model, where the method includes the following steps:
acquiring a power grid model to be calculated and relevant model information corresponding to the power grid model, and acquiring a topological structure of a power grid according to the power grid model and the relevant model information corresponding to the power grid model;
and determining the total number of days of cascading failure simulation mode simulation formed by the topological structure of the power grid, simulating by taking each day as a unit, obtaining the line number of the disconnected line output by each day of simulation after the total number of days of simulation is finished, further counting the number of the line numbers of the disconnected line output by each day of simulation, and outputting the disconnected line with the maximum number of the line numbers as the power grid power failure key line.
The relevant model information comprises reference voltage of a power grid, node information, generator information, line information and/or transformer branch information.
The method comprises the following specific steps of determining the total number of days of cascading failure simulation mode simulation formed by the topological structure of the power grid, simulating by taking each day as a unit, and obtaining the line number of a disconnected line output by each day of simulation after the total number of days of simulation is finished:
s21, acquiring the total number of days of simulation, and judging whether the total number of days of simulation is 0 or not;
s22, if the total number of days of the simulation is not 0, entering a cascading failure simulation mode to carry out simulation, outputting a line number of a disconnected line, reducing the total number of days of the simulation by one, and returning to the S21; the specific steps of entering a cascading failure simulation mode for simulation and outputting the line number of the open circuit include:
step S221, initializing the on-off probability of each line in the topological structure of the power grid to be P, initializing the number of the on-off lines to be 1, randomly sampling random numbers R which are uniformly distributed in a [0,1] interval, and determining the on-off lines with the on-off probability being greater than the random numbers R as the initial on-off lines; wherein P is between [0,1 ];
step S222, distinguishing each electric island in the topological structure of the power grid according to the initial cut-off line, and establishing a corresponding load flow calculation model for each electric island;
step S223, calculating a load flow calculation model of each electrical island by using an optimal direct current load flow method to obtain direct current load flows of lines contained in each electrical island;
step S224, judging whether the direct current power flow of one line in each electric island is larger than a preset heavy load threshold value; if yes, go to step S225; if not, jumping to step S227;
step S225, the lines with the direct current power flows larger than the preset heavy load threshold value are all cut off according to the probability of 1-beta, and the adjacent lines of each line with the direct current power flows larger than the preset heavy load threshold value are all cut off according to the random cut-off probability tau; wherein, beta and tau are both preset fixed values;
step S226, when the corresponding electrical island is determined to have an island after each line with the direct current flow larger than the preset overloading threshold value is cut off, resetting each island in the same electrical island as the electrical island, and returning to the step S223;
step S227, when the corresponding electrical island does not have an island after each line with the direct current flow larger than the preset heavy load threshold value is cut off, taking each line with the direct current flow larger than the preset heavy load threshold value as a final cut-off line in the day and outputting the corresponding line number;
and S23, if the total number of the simulated days is 0, outputting the line number of the disconnected line which is output in a simulation mode on each day.
Wherein the method further comprises:
determining the total number of days of cascading failure simulation mode simulation formed by the topological structure of the power grid, simulating by taking each day as a unit, obtaining a cascading failure accident chain and corresponding failure load loss corresponding to a broken line output by each day of simulation after the total number of days of simulation is finished, carrying out cumulative probability statistics according to the obtained failure load loss output by each day of simulation to obtain a probability density function of the power failure scale, and further calculating an index value for power failure risk evaluation according to the obtained probability density function of the power failure scale.
Wherein the indicator values include a risk value, a condition risk value, and a mathematical expectation of a power outage event.
The embodiment of the invention also provides a system for determining the power failure key line of the power grid based on the cascading failure model, which comprises the following steps:
the acquisition unit is used for acquiring a power grid model to be calculated and relevant model information corresponding to the power grid model, and acquiring a topological structure of a power grid according to the power grid model and the relevant model information corresponding to the power grid model;
and the first output unit is used for determining the total number of days of cascading failure simulation mode simulation formed by the topological structure of the power grid, simulating by taking each day as a unit, obtaining the line number of the broken line which is output in a simulation mode on each day after the total number of days of simulation is finished, further counting the number of occurrences of the obtained line number of the broken line which is output in a simulation mode on each day, and outputting the broken line with the maximum number of occurrences of the line number as the power grid power failure key line.
The relevant model information comprises reference voltage of a power grid, node information, generator information, line information and/or transformer branch information.
Wherein, still include:
and the second output unit is used for determining the total number of days of cascading failure simulation mode simulation formed by the topological structure of the power grid, simulating by taking each day as a unit, obtaining a cascading failure accident chain and corresponding failure load loss corresponding to a cut-off line output in each day of simulation after the total number of days of simulation is finished, performing cumulative probability statistics according to the obtained failure load loss output in each day of simulation to obtain a probability density function of the power failure scale, and further calculating an index value for power failure risk assessment according to the obtained probability density function of the power failure scale.
Wherein the index values include a risk value, a condition risk value, and a mathematical expectation of a power outage event.
The embodiment of the invention has the following beneficial effects:
1. according to the invention, the weak link of the power grid is pointed out through the accumulated on-off times of the line, so that a key line which has important influence on the cascading failure of the power system can be identified, data support is provided for line capacity expansion, and the reconstruction of the weak link of the power system is realized;
2. the method calculates index values (such as risk value, condition risk value and mathematical expectation of power failure accidents) for power failure risk assessment and carries out quantitative comparison to obtain a series of guidance measures beneficial to reducing power failure risk.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is within the scope of the present invention for those skilled in the art to obtain other drawings based on the drawings without inventive exercise.
Fig. 1 is a flowchart of a method for determining a power outage critical line of a power grid based on a cascading failure model according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an IEEE118 node system in an application scenario of a method for determining a power outage critical line of a power grid based on a cascading failure model according to an embodiment of the present invention;
fig. 3 is a cumulative probability density distribution diagram of a blackout accident in an application scenario of a method for determining a power grid blackout critical line based on a cascading failure model according to an embodiment of the present invention;
fig. 4 is a fault scale distribution graph under standard operating parameters in an application scenario of the method for determining a power grid blackout key line based on a cascading failure model according to the embodiment of the present invention;
fig. 5 is a fault scale distribution graph of different initial load levels in an application scenario of the method for determining a power grid blackout key line based on a cascading failure model according to the embodiment of the present invention;
fig. 6 is a fault scale distribution graph of different basic false operation probabilities in an application scenario of the method for determining a power outage critical line of a power grid based on a cascading failure model according to the embodiment of the present invention;
fig. 7 is a fault scale distribution graph of the present invention under different overload thresholds in an application scenario of a method for determining a power outage critical line of a power grid based on a cascading failure model according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of a system for determining a power outage critical line of a power grid based on a cascading failure model according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings.
As shown in fig. 1, in an embodiment of the present invention, a method for determining a critical line of a power outage of a power grid based on a cascading failure model is provided, where the method includes the following steps:
s1, acquiring a power grid model to be calculated and relevant model information corresponding to the power grid model, and acquiring a topological structure of a power grid according to the power grid model and the relevant model information corresponding to the power grid model;
the specific process is that a power grid model required to be calculated is imported, the model records relevant model information such as reference voltage, node information, generator information, line information and/or transformer branch information of a power grid in a matrix form, and the specific topological structure of the power grid can be determined according to the relevant model information.
In the embodiment of the invention, the IEEE118 node system in FIG. 2 is subjected to example calculation and analysis, so that the occurrence and propagation of the cascading failure of the power grid and the evolution process of the power grid can be visually reflected.
And S2, determining the total number of days of cascading failure simulation mode simulation formed by the topological structure of the power grid, simulating by taking each day as a unit, obtaining the line number of the broken line output in simulation on each day after the total number of days of simulation is finished, further counting the number of occurrences of the obtained line number of the broken line output in simulation on each day, and outputting the broken line with the maximum number of occurrences of the line number as the power grid power failure key line.
The specific process is that firstly, the total number of days of cascading failure simulation mode simulation formed by the topological structure of the power grid is determined, the simulation is carried out by taking each day as a unit, and after the total number of days to be simulated is finished, the specific steps of obtaining the line number of the cut-off line output by each day of simulation comprise:
s21, acquiring the total number of simulated days (such as 350 days), and judging whether the total number of simulated days is 0 or not;
s22, if the total number of simulated days is not 0, entering a cascading failure simulation mode to perform simulation, outputting a line number of a disconnected line, reducing the total number of simulated days by one, and returning to the S21; the specific steps of entering a cascading failure simulation mode for simulation and outputting a line number of a cut-off line include:
s221, the disconnection probability of each line in the topological structure of the initial power grid is P, the number of the disconnected lines is 1, random numbers R which are uniformly distributed in a [0,1] interval are randomly sampled, and the disconnected lines with the disconnection probability larger than the random numbers R are determined to be the initial disconnected lines; wherein P is between [0,1 ]; it should be noted that, by using the monte carlo sampling technique, the probability P is used to determine whether a certain line will be disconnected during the cascading failure. When P =0, it indicates that a certain line in the topology structure of the power grid is not disconnected all the time; when P =1, it indicates that a certain line in the topology of the power grid is broken during the everyday evolution process. In order to simplify the processing and improve the simulation efficiency, all the lines P =1 in the initial fault stage are set, and the upper limit of the number of the initial lines to be opened is 1, that is, in the initial stage, one line is necessarily randomly designated as the initial fault to be opened.
Step S222, distinguishing each electric island in a topological structure of a power grid according to an initial cut-off line, and establishing a corresponding load flow calculation model for each electric island; that is, an electrical island is generated after any one line is disconnected, data of all the electrical islands are separately stored into a power grid model in the same shape as that of the step S221, and the data are convenient to perform next-step load flow calculation respectively;
step S223, calculating a load flow calculation model of each electrical island by using an optimal direct current load flow method to obtain direct current load flows of lines contained in each electrical island; it should be noted that the power flow calculation model is existing in the field and is not described herein again, and the direct current power flow of the line includes a line load rate, and the line load rate is obtained by dividing the active power of all lines obtained through power flow calculation by the rated capacity of the corresponding line;
step S224, judging whether the direct current power flow of one line in each electric island is larger than a preset heavy load threshold value; if yes, go to step S225; if not, jumping to step S227; wherein the preset reloading threshold α =0.99;
step S225, the lines with the direct current power flows larger than the preset heavy load threshold value are all cut off according to the probability of 1-beta, and the adjacent lines of each line with the direct current power flows larger than the preset heavy load threshold value are all cut off according to the random cut-off probability tau; wherein, beta and tau are both preset fixed values; beta is the false action rate beta =0.001 of the protection device, and tau is the random on-off probability tau =0.0007;
step S226, when the corresponding electrical island has an island after each line with the direct current power flow larger than the preset overloading threshold is cut off, resetting each island in the same electrical island as the electrical island, and returning to the step S223; namely, the line is disconnected, the grid disconnection is caused, a new electrical island is formed, and the steps S222 to S224 need to be repeated again;
step S227, when the corresponding electric island does not have an island after each line with the direct current flow larger than the preset heavy load threshold value is cut off, taking each line with the direct current flow larger than the preset heavy load threshold value as a final cut-off line in the day and outputting the corresponding line number; if the island is not generated and the circuit is not disconnected, the same day cascading failure simulation mode is terminated;
and S23, if the total number of the simulated days is 0, outputting the line number of the disconnected line which is output in a simulation mode on each day.
It should be noted that, after the end of the daily cascading failure simulation mode and before the start of the next day cascading failure simulation mode, the increase of the load and the power generation capacity of the power grid and the transformation and upgrading of the line by the power grid can be simulated, and the transformation of the weak link of the power system is realized through the updating of the capacity of the load, the generator and the weak line. For example, the increase of the grid load and the power generation capacity are simulated by respectively multiplying the active load in the load information matrix in the grid model and the active output upper limit in the generator information matrix by an increase factor λ = 1.0005; for another example, the load rated capacity of the line information matrix corresponding to the line which is disconnected due to overload on the same day is multiplied by a line transmission capacity growth factor μ =1.005, and the transformation and upgrading of the line by the power grid are simulated.
In the embodiment of the present invention, the simulation data further includes a daily cascading failure accident chain and a corresponding failure load loss, and the power outage risk assessment and the power grid weak link finding out may also be performed according to the daily failure load loss, so the method further includes:
determining the total number of days of cascading failure simulation mode simulation formed by a topological structure of a power grid, simulating by taking each day as a unit, obtaining a cascading failure accident chain and corresponding failure load loss corresponding to a broken line output by each day of simulation after the total number of days of simulation is finished, carrying out cumulative probability statistics according to the obtained failure load loss output by each day of simulation to obtain a probability density function of the power failure scale, and further calculating an index value for power failure risk evaluation according to the obtained probability density function of the power failure scale; wherein the index values include a risk value, a condition risk value, and a mathematical expectation of a power outage event.
It should be noted that, the cumulative probability statistics is to divide the fault load loss from the minimum loss value to the maximum loss value into finite small intervals, count the number of times of the power failure events falling into each interval respectively, divide the number by the total number of the power failure events to obtain the probability value of the corresponding interval, and obtain the probability density function p (x) of the power failure scale after statistics through fitting of the ksdensity function in Matlab.
The three index values can be calculated by using mathematical formulas (2) to (4), and the calculation is as follows:
Figure GDA0003983001230000081
Figure GDA0003983001230000082
Figure GDA0003983001230000083
where VaR is the Risk value, CVaR is the conditional Risk value, and Risk is the load loss expectation value.
As shown in fig. 3 to fig. 7, an application scenario of the method for determining a power outage critical line of a power grid based on a cascading failure model in the embodiment of the present invention is further described:
the cumulative probability density distribution of the blackout accident obtained through simulation calculation statistics is shown in fig. 3, and the fault scale distribution curve in fig. 3 obviously has the long tail characteristic of power law distribution, which means that the cascading failure model has the risk of the catastrophic accident with serious consequences because small probability cannot be ignored.
If the common coordinate axis of FIG. 3 is changed into a logarithmic coordinate axis, the power law characteristic of the simulation result is more visual and clear, and the fault scale distribution curve under the logarithmic coordinate axis is the fault scale distribution curve under the standard operation parameters shown in FIG. 4;
next, the confidence interval σ =0.99 is taken, and the Risk value (VaR), the conditional Risk value (CVaR), and the load loss expectation value (Risk) are calculated by equations (2) to (4), and the results are shown in table 1 below:
TABLE 1
Figure GDA0003983001230000084
Figure GDA0003983001230000091
At this time, the physical meaning of the risk value is that in 3500-day simulation results of the model, the power failure scale of 99.0% is smaller than 1036.257MW; the physical implication of the conditional risk value is that the average excess loss of a power outage greater than 1036.257MW is 24.408MW. The load loss expectation takes into account the mathematical expectation of the outage risk for all sizes, whereas CVaR reflects the risk of large-scale outage in comparison.
Fig. 5 shows the distribution curves of the fault sizes when the initial load levels are different and the other operation parameters are the same (all are standard operation parameters), and table 2 below is the power outage risk assessment calculated according to the three distribution curves:
TABLE 2
Figure GDA0003983001230000092
Fig. 5 and table 2 together show that the initial load level will largely affect the fault scale distribution, and the higher the initial load level is, the larger the scale and frequency of the power failure accident of the system will be, and the overall fault risk or the major power failure fault risk is obviously improved.
Fig. 6 shows distribution curves of the fault scale with different basic false operation probabilities and the same other operation parameters, and table 3 below is a power outage risk assessment calculated according to the three distribution curves:
TABLE 3
Figure GDA0003983001230000093
The results in fig. 6 and table 3 show that the larger the basic false action probability is, the higher the outage Risk is, but the different basic false action probabilities mainly affect the values of VaR and Risk, and have little influence on CVaR, which means that the increase of the basic false action probability within a certain range does not increase the Risk of large outage accident, but increases the Risk of medium and small scale outage accident.
Fig. 7 shows the distribution curves of the fault sizes under different line heavy load thresholds, and table 4 below is the power outage risk assessment calculated according to three distribution curves:
TABLE 4
Figure GDA0003983001230000094
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Figure GDA0003983001230000101
The results of fig. 7 and table 4 show that lowering the line reload threshold significantly increases the risk of a blackout event in the power system.
Finally, 5 lines with the highest cumulative number of disconnections in 3500-day simulation are counted, as shown in table 5 below
TABLE 5
Figure GDA0003983001230000102
The lines listed in table 5 are disconnected many times along with the evolution of the network, and particularly, the two lines 77-78 and 79-80 are disconnected up to 306 times in total, which indicates that the two lines are key lines causing major power failure of the IEEE118 node system and are weak links of the system. For an actual system, expansion of a relevant line needs to be considered preferentially.
As shown in fig. 8, in an embodiment of the present invention, a system for determining a critical line of a power outage of a power grid based on a cascading failure model includes:
the acquiring unit 10 is configured to acquire a power grid model to be calculated and relevant model information corresponding to the power grid model, and obtain a topology structure of a power grid according to the power grid model and the relevant model information corresponding to the power grid model;
the first output unit 20 is configured to determine the total number of days of the cascading failure simulation mode simulation formed by the topology structure of the power grid, perform simulation in units of each day, obtain the line number of the disconnected line that is output in the simulation on each day after the total number of days of the simulation is finished, further count the number of occurrences of the line number of the disconnected line that is obtained in the simulation on each day, and output the disconnected line with the largest number of occurrences of the line number as the power grid outage key line.
The relevant model information comprises reference voltage of a power grid, node information, generator information, line information and/or transformer branch information.
Wherein, still include:
the second output unit 30 is configured to determine a total number of days of cascading failure simulation mode simulation formed by the topology structure of the power grid, perform simulation on the total number of days per day, obtain a cascading failure accident chain and a corresponding failure load loss corresponding to a disconnected line that are output in each simulation after the total number of days of simulation is finished, perform cumulative probability statistics according to the obtained failure load loss that is output in each simulation, obtain a probability density function of the power outage scale, and further calculate an index value for power outage risk assessment according to the obtained probability density function of the power outage scale.
Wherein the index values include a risk value, a condition risk value, and a mathematical expectation of a power outage event.
The embodiment of the invention has the following beneficial effects:
1. according to the method, the weak link of the power grid is pointed out through the accumulated on-off times of the line, the key line which has important influence on the cascading failure of the power system can be identified, data support is provided for line capacity expansion, and the transformation of the weak link of the power system is realized;
2. the method calculates index values (such as risk value, condition risk value and mathematical expectation of power failure accidents) for power failure risk assessment and carries out quantitative comparison to obtain a series of guidance measures beneficial to reducing power failure risk.
It should be noted that, in the above system embodiment, each included unit is only divided according to functional logic, but is not limited to the above division as long as the corresponding function can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It will be understood by those skilled in the art that all or part of the steps in the method for implementing the above embodiments may be implemented by relevant hardware instructed by a program, and the program may be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc.
While the invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not to be limited to the disclosed embodiment, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims (7)

1. A method for determining a power grid blackout key line based on a cascading failure model is characterized by comprising the following steps:
acquiring a power grid model to be calculated and relevant model information corresponding to the power grid model, and acquiring a topological structure of a power grid according to the power grid model and the relevant model information corresponding to the power grid model;
determining the total number of days of cascading failure simulation mode simulation formed by the topological structure of the power grid, simulating by taking each day as a unit, obtaining the line number of the disconnected line output by each day of simulation after the total number of days of simulation is finished, further counting the number of the line number of the disconnected line output by each day of simulation, and outputting the disconnected line with the maximum number of the line number as the power grid power failure key line;
wherein the method further comprises:
determining the total number of days of cascading failure simulation mode simulation formed by the topological structure of the power grid, simulating by taking each day as a unit, obtaining a cascading failure accident chain and corresponding failure load loss corresponding to a broken line output by each day of simulation after the total number of days of simulation is finished, performing cumulative probability statistics according to the obtained failure load loss output by each day of simulation to obtain a probability density function of the power failure scale, and further calculating an index value for power failure risk evaluation according to the obtained probability density function of the power failure scale.
2. The cascading failure model-based method for determining the critical line of the grid blackout as claimed in claim 1, wherein the relevant model information comprises a reference voltage of the grid, node information, generator information, line information and/or transformer branch information.
3. The method for determining a critical line of a power failure of a power grid based on a cascading failure model according to claim 1, wherein the specific steps of determining the total number of days of a cascading failure simulation mode simulation formed by the topological structure of the power grid, performing simulation by taking each day as a unit, and obtaining the line number of the disconnected line output by each day of simulation after the total number of days of the simulation is over comprise:
s21, acquiring the total number of days of simulation, and judging whether the total number of days of simulation is 0 or not;
s22, if the total number of days of the simulation is not 0, entering a cascading failure simulation mode to carry out simulation, outputting a line number of a disconnected line, reducing the total number of days of the simulation by one, and returning to the S21; the specific steps of entering a cascading failure simulation mode for simulation and outputting the line number of the open circuit include:
step S221, initializing the on-off probability of each line in the topological structure of the power grid to be P, initializing the number of the on-off lines to be 1, randomly sampling random numbers R which are uniformly distributed in a [0,1] interval, and determining the on-off lines with the on-off probability being greater than the random numbers R as the initial on-off lines; wherein P is between [0,1 ];
step S222, distinguishing each electric island in the topological structure of the power grid according to the initial cut-off line, and establishing a corresponding load flow calculation model for each electric island;
step S223, calculating a load flow calculation model of each electrical island by using an optimal direct current load flow method to obtain direct current load flows of lines contained in each electrical island;
step S224, judging whether the direct current power flow of one line in each electric island is larger than a preset heavy load threshold value; if yes, go to step S225; if not, jumping to step S227;
step S225, all lines with the direct current power flows larger than a preset heavy-load threshold are cut off according to the probability of 1-beta, and adjacent lines of each line with the direct current power flows larger than the preset heavy-load threshold are cut off according to the random cut-off probability tau; wherein, beta and tau are both preset fixed values;
step S226, when the corresponding electrical island has an island after each line with the direct current power flow larger than the preset overloading threshold is cut off, resetting each island in the same electrical island as the electrical island, and returning to the step S223;
step S227, when the corresponding electric island does not have an island after each line with the direct current flow larger than the preset heavy load threshold value is cut off, taking each line with the direct current flow larger than the preset heavy load threshold value as a final cut-off line in the day and outputting the corresponding line number;
and S23, if the total number of the simulated days is 0, outputting the line number of the disconnected line which is output in a simulation mode on each day.
4. The method for determining a critical line of a power grid outage based on a cascading failure model of claim 1, wherein the index values include a risk value, a conditional risk value, and a mathematical expectation of the outage event.
5. A system for determining a power grid blackout key line based on a cascading failure model is characterized by comprising:
the acquisition unit is used for acquiring a power grid model to be calculated and relevant model information corresponding to the power grid model, and acquiring a topological structure of a power grid according to the power grid model and the relevant model information corresponding to the power grid model;
the first output unit is used for determining the total number of days of cascading failure simulation mode simulation formed by the topological structure of the power grid, simulating by taking each day as a unit, obtaining the line number of the disconnected line output by each day of simulation after the total number of days of simulation is finished, further counting the number of the obtained line number of the disconnected line output by each day of simulation, and outputting the disconnected line with the maximum number of the line number as the power grid power failure key line;
wherein, still include:
and the second output unit is used for determining the total number of days of cascading failure simulation mode simulation formed by the topological structure of the power grid, simulating by taking each day as a unit, obtaining a cascading failure accident chain and corresponding failure load loss corresponding to a cut-off line output in each day of simulation after the total number of days of simulation is finished, performing cumulative probability statistics according to the obtained failure load loss output in each day of simulation to obtain a probability density function of the power failure scale, and further calculating an index value for power failure risk assessment according to the obtained probability density function of the power failure scale.
6. The cascading failure model-based grid blackout critical line determination system of claim 5, wherein the relevant model information comprises a reference voltage of the grid, node information, generator information, line information, and/or transformer branch information.
7. The cascading failure model-based system for determining grid blackout critical lines of claim 5, wherein the index values comprise a risk value, a condition risk value, and a mathematical expectation of a blackout incident.
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